Genetic control of mesophyll conductance in common wheat

Recent interest in mesophyll conductance (gm) has revealed a dynamic leaf trait that significantly limits photosynthetic rate and influences leaf water-use efficiency (Flexas et al., 2008, 2013; Douthe et al., 2011; Evans & von Caemmerer, 2013). Traditional methods of estimating gm are slow, technically challenging and error-prone (Warren, 2006; Evans, 2009), but the recent development of online stable carbon isotope discrimination (∆13CA) measurement systems coupled to leaf gas exchange have removed some of these measurement problems (Barbour et al., 2007, 2010; Tazoe et al., 2009). Taking advantage of relatively rapid gm measurements available with online ∆13CA, we explored the genetic control of gm within a wheat mapping population and were able to identify a quantitative trait locus (QTL) responsible for 9% of variation in gm. This preliminary study demonstrates that we can now investigate the genetic control of gm, and that further study across multiple mapping populations and growth environments is warranted to confirm the QTL and identify the gene(s). After CO2 has diffused through stomatal pores and into the leaf intercellular air space, it must also diffuse through the cell walls, through the plasma membrane, the cytosol and finally the chloroplast envelope before it can be fixed by RuBisco (Evans et al., 2009). The inverse of combined resistances to CO2 diffusion from the intercellular air space to the sites of fixation is termed mesophyll conductance (gm). There has been considerable recent research in gm, revealing that gm is a significant limitation to photosynthesis (Warren et al., 2003; Niinemets et al., 2009), responds to environmental conditions (Flexas et al., 2007; Warren, 2008; Douthe et al., 2011; Evans & von Caemmerer, 2013; von Caemmerer & Evans, 2015), is variable between genotypes of the same species (Barbour et al., 2010; Gu et al., 2012; Jahan et al., 2014) and contributes to leaf water-use efficiency (Flexas et al., 2013). Leaves with high surface area of chloroplasts exposed to the intercellular air space tend to have higher gm (Evans & von Caemmerer, 1996; Tomás et al., 2013) and leaves with thick cell walls tend to have lower gm (Tomás et al., 2013), and gm has also been found to vary in plants with altered expression of aquaporin (Uehlein et al., 2003, 2008; Hanba et al., 2004). This aquaporin relationship provides a potential mechanism for the observed rapid response of gm to environmental conditions (Tazoe et al., 2011). However, very little is known about genetic control of gm, despite a growing number of studies highlighting the contribution of gm to traits of agronomic importance like photosynthesis and water-use efficiency. Gu et al. (2012) investigated leaf gas exchange in 11 rice introgression lines using a multiple regression analysis, and found that under well-watered conditions variation in gm explained a significant proportion of variation in photosynthetic rate. There have been no studies to date that have directly tested the genetic control of gm in any species. Hence, our study aimed to demonstrate that the current tools allow the assessment of the genetic control of gm in wheat. Six replicate plants of 150 Cranbrook/Halberd doubled haploid (DH) lines of the common wheat (Triticum aestivum L.) mapping population and the two parental lines were grown for 5 wk in controlled environment rooms. The temperature inside the growth rooms was set at 25°C during the 14 h light period, and 17°C in the dark. Relative humidity was maintained at 75–80% and photosynthetically active radiation was 600 μmol m−2 s−1 at the upper leaves. Seeds were planted in 8 l pots with potting mix amended with slow-release fertilizer (Osmocote Exact, Scotts, Sydney, NSW, Australia). Plants were thinned to two per pot at week three. Gas exchange measurements could be made on a maximum of 30 plants each day, so planting was staggered in time to allow all plants to be measured at the same days after planting and developmental stage. Measurements on the 912 plants took 6 wk. A coupled leaf gas exchange/∆13CA measurement system was used to measure photosynthetic rate (A), stomatal conductance (gs), leaf intrinsic water-use efficiency (A/gs) and gm. Two Li6400xt photosynthesis systems (Li-Cor Inc., Lincoln, NE, USA) fitted with 6 cm2 leaf chambers and red–blue light sources were connected to a tunable diode laser absorption spectrometer (TDLAS, model TGA100A, Campbell Scientific Inc., Logan, UT, USA) as described by Barbour et al. (2007, 2010). The CO2 mole fraction inside the leaf cuvette was controlled at 400 μmol mol−1, leaf temperature at 25°C, and irradiance at 2000 μmol m−2 s−1 for all leaves. Relative humidity was not controlled, and varied between leaves from 72% to 80% (leaf-to-air vapour pressure difference, VPd, varied between 0.63 and 0.92 kPa). Two of the youngest, fully expanded leaves from each plant were placed side-by-side in the leaf cuvette and remained in the cuvette until gas exchange and isotope compositions stabilized (20–40 min). Mesophyll conductance was estimated from gas exchange and ∆13CA as described by Barbour et al. (2010), but including ternary effects (Farquhar & Cernusak, 2012). Assumptions were required to apply the equations; we assumed that isotope fractionation during carboxylation was 29‰, fractionation during photorespiration was 16.2‰, fractionation during dissolution and diffusion through water was 1.8‰, fractionation during day respiration was −3‰, the rate of day respiration at 25°C was 2.2 μmol m−2 s−1 (Jahan et al., 2014) and the CO2 compensation point in the absence of day respiration was 37.5 μmol mol−1. An analysis of variance (ANOVA) in Genstat, 16th edn (VSN International Ltd, London, UK) revealed a significant effect of the time of day at which measurements were made (a general linear decline in gs and gm over the course of the day, a slight increase in A and an increase in A/gs), so time of measurement was treated as a covariate and means of gas exchange parameters were adjusted accordingly. The covariate-adjusted means were very similar to numerical means for A and gs (mostly < 5% change), but changed more for gm (up to a 44% change, and a 14% change on average). A genetic map with 1325 loci for the population is described in Lehmensiek et al. (2005). The composite interval mapping function in QTL Cartographer 2.5 (Wang et al., 2007) was used, carrying out 1000 permutations with 2 cM steps at P = 0.01 to detect QTL. Among the doubled haploid lines, photosynthetic rate and stomatal conductance varied from 22.4 to 35.3 μmol m−2 s−1 and 0.50 to 1.30 mol m−2 s−1, with means of 29.4 μmol m−2 s−1 and 0.79 mol m−2 s−1, respectively (Fig. 1). The two parental lines, Cranbrook and Halberd, had A of 29.1 ± 2.2 and 25.4 ± 0.7 μmol m−2 s−1 and gs of 0.62 ± 0.08 and 0.81 ± 0.07 mol m−2 s−1, respectively (mean ± standard error (SE), n = 6). These values for gas exchange in wheat are high (cf. Fischer et al., 1998), but consistent with nonlimiting growth conditions, and high light, low VPd measurement conditions (Jahan et al., 2014). Mesophyll conductance varied three-fold, 0.27–0.94 mol m−2 s−1 bar−1, with a mean of 0.55 mol m−2 s−1 bar−1. The two parental lines, Cranbrook and Halberd, had gm of 0.71 ± 0.13 and 0.44 ± 0.07 mol m−2 s−1 bar−1, respectively (mean ± SE, n = 6). Cranbrook had significantly higher leaf intrinsic water-use efficiency than Halberd (P = 0.009) due to both higher A and lower gs (Fig. 1). This cultivar ranking is the same as the ranking of these two cultivars for water-use efficiency estimated from leaf carbon isotope discrimination (∆13Cl) in field trials over multiple seasons and sites (Rebetzke et al., 2008). This ranking differs from that reported by Jahan et al. (2014) due to a reversal in ranking of gs and gm between genotypes. The reason for the difference in genotype rankings for gs and gm between experiments may relate to differences in leaf age, and measurement light and VPd between the two experiments (younger leaves were measured at a lower VPd and higher light in the current experiment). Both gs and gm are known to respond to short-term changes in environmental conditions (Flexas et al., 2008). Mesophyll conductance was positively, but not closely, related to photosynthetic rate across the genotypes (gm = 0.024A − 0.08, R = 0.36, P < 0.0001; data not shown), but was unrelated to stomatal conductance (P > 0.05). The observation that stomatal conductance and mesophyll conductance are not correlated is important because the most useful combination of traits for improving water-use efficiency while maintaining productivity would be high gm, to allow high A, but low gs (Barbour et al., 2010). Of course, leaf intrinsic water-use efficiency would need to scale to grain water-use efficiency, a link that remains unclear (Rebetzke et al., 2013). In this study, gm was positively, but again not strongly, related to leaf-intrinsic water-use efficiency (gm = 0.011A/gs − 0.18, R = 0.42, P < 0.0001; data not shown). That is, variability in gm explained 18% of observed variability in A/gs. All else being equal (i.e. if gm varied but gs and photosynthetic capacity did not), we would expect a positive relationship between A/gs and gm due to increased chloroplastic CO2 concentration allowing increased A at higher gm. Positive relationships between gm and A/gs have been observed for a number of species (Flexas et al., 2013). QTL analysis revealed a region on the long arm of chromosome 2A containing a QTL for gm with a limit of detection (LOD) score of 3.07, which explained 9% of variation in gm within the population (Table 1). This is the first report of a QTL for gm in any species. While this level of genetic control is not strong, and comes from a single mapping population grown in a single (controlled) environment, the result is statistically significant and important for a complex trait such as gm. The molecular marker of interest, PSR540, is in the same region as marker wmc170. Marker wmc170 lies close to a gene for sodium exclusion in a salt-tolerant genotype of durum wheat (Munns et al., 2003), a gene later identified as HKT1;4 (Huang et al., 2006). The active HKT1;4 allele is not present in modern wheat. The broad region of interest on chromosome 2A has synteny to rice chromosome 4 (Gale & Devos, 1998). Based on this synteny, Forrest & Bhave (2010) identified copies of a number of wheat aquaporin genes within this region through in silico mapping. These genes are of particular interest because aquaporin are thought to transport CO2 through membranes (Hanba et al., 2004; Uehlein et al., 2008). Carbon dioxide must cross the plasma membrane and chloroplast envelope to reach the chloroplast stroma, so it is possible that aquaporin within the plasma membrane could influence gm (sensu Uehlein et al., 2008). Many wheat aquaporin have been localized to the plasma membrane (Forrest & Bhave, 2008), including those mapped to chromosome 2 (e.g. TaPIP2;3, TaTIP3;2 and TaTIP2;1). The in silico map of Forrest & Bhave (2010) does not predict specific locations of genes on chromosomes, so a molecular genetic study seems warranted to confirm the gene location, identity and function. Setting aside the exciting result of the first QTL for gm, it is also pleasing that this study identified three QTL for leaf intrinsic water-use efficiency, on 3B, 5A and 7A. The QTL on 3B coincides with a QTL for carbon isotope discrimination as recorded in whole leaf tissue (∆13Cl) identified for this mapping population by Rebetzke et al. (2008). The linked marker, P40/M54-7, identified here is in the same location as markers glk683 and wm1-1A found in the Rebetzke et al. (2008) study. Leaf carbon isotope discrimination (∆13Cl) has been extensively used as a proxy for water-use efficiency, particularly in wheat (Farquhar & Richards, 1984; Condon et al., 1987), because both ∆13Cl and A/gs depend on the control of CO2 and H2O diffusion through stomata. This study provides further support for carbon isotope discrimination theory and evidence of the underlying genetic control of ∆13Cl in wheat. Here we report the first hints of genetic control of mesophyll conductance. Relatively rapid gm measurement techniques combined with recently developed molecular genetic tools provide the opportunity to understand genetic control of gm in plants and improve the likelihood of using this trait to improve crop productivity and water-use efficiency. We note that, although not used here, combined measurements of leaf gas exchange and chlorophyll fluorescence using the ‘variable J’ method developed by Di Marco et al. (1990) and Harley et al. (1992) will also give rapid measurements of gm (although typically over a smaller leaf area and with considerable sensitivity to errors in the estimation of the CO2 compensation point in the absence of day respiration, Pons et al., 2009, than the ∆13CA technique). We trust that this preliminary study will prompt further studies on the topic using multiple mapping populations grown in a range of environmental conditions. This research was supported by the Grains Research and Development Corporation (US00056) and the Australian Research Council through a Future Fellowship to MMB (FT0992063). S. Ryazanova and W. Lin are thanked for technical support and Dr R. Munns for valuable discussion.